Random variations or anomalies in consumer demand that defy seasonality or trends are referred to as “noise in demand.” Forecasting and inventory planning are made more difficult by this unpredictability, which frequently results in excess safety stock or stockouts. Inventory optimization is improved by using advanced analytics and smoothing techniques to reduce noise and increase the accuracy of demand signals.
